Occupant sensing systems are commonly used in motor vehicles for purposes of determining if pyrotechnically deployed restraints such as air bags should be deployed in the event of sufficiently severe crash. Early systems relied exclusively on sensors for measuring physical parameters such as seat force, but vision-based systems have become economically attractive due to the advent of low-cost solid-state imaging chips. Also, the required image capture rate is relatively low (one frame per second, for example) compared to most imaging applications, allowing adequate sensing performance with limited memory and image processing capability. However, lighting conditions in a vehicle passenger compartment can change significantly from frame to frame with such slow image capture rates, and it is important to ensure that the captured images always remain within the dynamic range of the imaging chip. This problem can be addressed in part by actively illuminating the region of interest with an array of infrared LEDs, for example, but the required LED power consumption can be a significant drawback. Accordingly, it is preferable to minimize the use of active illumination, and to adapt to ambient illumination changes in some other way, while preserving the cost benefits associated with limited memory size and image processing capability.